Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unk...Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unknown gray nodes, and the second the evolution gray nodes. The relevant definitions are also given. Further- more, grayness degree in complex networks is described and divided into two forms--the relative grayness degree （RGD） and the absolute grayness degree （AGD）, which are proved respectively.展开更多
为解决贫信息背景下对系统进行故障模式、影响及危害性分析(failure mode,effects and criticality analysis,FMECA)受故障信息少、故障数据部分未知等问题限制,同时为有限定量危害性矩阵分析方法的缺陷,提出了适用于贫信息背景的灰FMEC...为解决贫信息背景下对系统进行故障模式、影响及危害性分析(failure mode,effects and criticality analysis,FMECA)受故障信息少、故障数据部分未知等问题限制,同时为有限定量危害性矩阵分析方法的缺陷,提出了适用于贫信息背景的灰FMECA模型。首先对危害性矩阵图进行规范化改进,统一横纵坐标轴量纲,提出危害度权重比概念以规范作图比例;然后在危害度计算中引入区间灰数,提出矩域灰点概念以表征故障模式难以确知的危害性;最后依照不确定型决策思想给出矩域灰点的一般排序规则,为贫信息背景的故障模式危害性排序提供解决方案。通过某航天飞机主发动机高压燃料涡轮泵进行案例研究,验证了所提模型的有效性。展开更多
基金Supported by the National Natural Science Foundation of China(71110307023)~~
文摘Based on the theory of complex network and gray system, the sugesstion that there exist two types of gray nodes in complex networks, Gray Node I and Gray Node II, is concluded. The first one refers to the existent unknown gray nodes, and the second the evolution gray nodes. The relevant definitions are also given. Further- more, grayness degree in complex networks is described and divided into two forms--the relative grayness degree （RGD） and the absolute grayness degree （AGD）, which are proved respectively.
文摘为解决贫信息背景下对系统进行故障模式、影响及危害性分析(failure mode,effects and criticality analysis,FMECA)受故障信息少、故障数据部分未知等问题限制,同时为有限定量危害性矩阵分析方法的缺陷,提出了适用于贫信息背景的灰FMECA模型。首先对危害性矩阵图进行规范化改进,统一横纵坐标轴量纲,提出危害度权重比概念以规范作图比例;然后在危害度计算中引入区间灰数,提出矩域灰点概念以表征故障模式难以确知的危害性;最后依照不确定型决策思想给出矩域灰点的一般排序规则,为贫信息背景的故障模式危害性排序提供解决方案。通过某航天飞机主发动机高压燃料涡轮泵进行案例研究,验证了所提模型的有效性。
